Citations of ACLA Prizewinning Scholarship
Bibliographic record
Abstract
With this issue, Comparative Literature Studies publishes, for the first time in print, the language used in praising scholarship in various formats as presented at the 2011 ACLA annual convention, held in Vancouver. The prizes mentioned here are the 2011 Harry Levin Prize for best book of literary criticism (along with the runners-up), the 2011 Charles Bernheimer Prize for best dissertation, the 2011 Horst Frenz Prize for best paper by a graduate student, and the 2011 Presidential Master’s Prize. These citations have been collectively authored by the respective prize committees of the ACLA. Committee members’ names can be found on the ACLA website (www.acla.org).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.040 | 0.049 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.028 | 0.008 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.143 | 0.057 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".